Ask stories

Share your information if you are looking for work. Please use this format:

  Location:
  Remote:
  Willing to relocate:
  Technologies:
  Résumé/CV:
  Email:

Readers: please only email these addresses to discuss work opportunities.

There's a site for searching these posts at https://www.wantstobehired.com.

Please state the location and include REMOTE for remote work, REMOTE (US) or similar if the country is restricted, and ONSITE when remote work is not an option.

Please only post if you personally are part of the hiring company—no recruiting firms or job boards. One post per company. If it isn't a household name, explain what your company does.

Please only post if you are actively filling a position and are committed to replying to applicants.

Commenters: please don't reply to job posts to complain about something. It's off topic here.

Readers: please only email if you are personally interested in the job.

Searchers: try https://dheerajck.github.io/hnwhoishiring/, http://nchelluri.github.io/hnjobs/, https://hnresumetojobs.com, https://hnhired.fly.dev, https://kennytilton.github.io/whoishiring/, https://hnjobs.emilburzo.com, or this (unofficial) Chrome extension: https://chromewebstore.google.com/detail/hn-hiring-pro/mpfal....

Don't miss this other fine thread: Who wants to be hired? https://news.ycombinator.com/item?id=46857487

What is the common thread among tech debt-crippled companies you've worked in? Not enough man hours to pay it down, difficulty to align engineering's willingness to pay it down with product's focus on new features, or something else? How can it be that, in the age of AI code gen, we haven't yet managed to solve this once and for all?

Inspired by this Ask HN: https://news.ycombinator.com/item?id=46834977

But I'm going further back in time to see if there is anybody here who still uses slide rules?

I feel crazy to ask. Over my lifetime, I have seen endless bookmark and read-it-later apps come and go. I've done research today, and most of the things I come across are dead and gone, or seem abandoned somehow. I'm aware of Instapaper. I haven't tried it (yet).

Here are some thoughts on what might fit my personal taste: - lightweight - very cheap - self-hosting might be nice, since I have a VPS currently - I'd like to easily dump an open tab into a backlog, and get reminded about it later: maybe I go to the app, maybe I get a daily email of suggestions. If I don't feel like reading the page, I can "snooze" it or otherwise put it back in the backlog (or drop it)

I think that's all I really want. I don't need notes or AI summaries or multiple apps for multiple devices, etc.

I might just build it, but curious if anyone has something they love.

Thanks!

I’ve noticed that most physical scientific and graphing calculators are easily outdone in terms of performance, capability and ease of use by the likes of Desmos and the default calculators on OS’es like the iOS, Android, and Windows.

It kind of makes me wonder whether people still use physical calculators from Texas Instruments, Casio, etc

If you do, I’d love to know why and how it is different/better for you than the ones I’ve mentioned and others like them and vice verse.

Cheers!

"Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it"

This has been a timely PSA.

Hey HN,

I'm on a quest for a distraction-free writing device and considering a super cheap laptop which I can just run vim/nano on.

I'd like: - Excellent battery life - Good keyboard - Sleep/wake capabilities (why is this so hard with Linux?)

I'm thinking some kind of chromebook? Maybe an old thinkpad?

I've been working on an SMTP/email server lately, and while Google and some others imply a lot of frowny-faces and put quotation marks around tests "passing" for not using a corporate relay, does at least let me communicate with the broader ecosystem.

Phone calls, however, seem like a tougher nut to crack. SIP URIs would let me kinda-sorta communicate with the broader ecosystem, but many phones and software seem to have dropped support for it; only a tiny % of those typically using the PSTN (that is, a "normal phone") would be able to call or receive calls to/from my addresses -- but it would be able to be directly and neatly integrated into the email server, which is a big plus.

I will probably still implement SIP URIs and VOIP support into the email server on principle, but I wonder if anyone has any alternatives to consider. Ideally, I would be able to communicate on the PSTN, but this seems like a lost cause.

Also curious about anyone using VOIP for work whether or not they allow or block SIP URIs from external networks. I maintained our VOIP server at work more than a decade ago, but it was a "side-project" due to working at an SMB where I wore many hats and couldn't specialize in anything; I wasn't even aware of SIP URIs at the time.

This is really weird. Google requires everyone to make a youtube channel before they can use youtube. Everything has been going fine for years and now somehow my channel, which never had a video and I was not even aware existed, was terminated and now I cannot use youtube at all. Appealing failed. This make no sense. how can I lose my channel when I never used it? Is there anyway to recover my channel subscriptions or use youtube without the channel?

My Google account has been suspended from GCP since March 2024.

I have submitted multiple appeals through ts-consult@google.com over 2 years. Every time I get the same automated template asking me to explain, I reply with details, then nothing. No human ever responds.

Case: #1-8622000037271

Timeline: - March 2024: Suspended, appeal submitted - April 2024: Automated requests for info, I replied - Nov 2024: More automated emails, I replied again - Dec 2024 - now: Complete silence

I am a CS researcher at UC Berkeley. This has seriously impacted my work.

Has anyone successfully gotten Google to review a GCP suspension appeal? How do you reach a human?

Status page shows it's up (https://status.signal.org).

Edit: status now updated to "Signal is experiencing technical difficulties. We are working hard to restore service as quickly as possible.")

Running OpenClaw with Anthrophic API and it burned through ~USD 50 in one day.

What are other OpenClaw users seeing? Anyone found effective ways to cut costs (model tiering, caching, etc.)?

New projects, refactors, experiments, startups, or late-night hacks — tell us what you’re building or exploring this month and why.

Hi everyone,

I’m building Persona, a platform to delegate email scheduling to AI. Lately, I’ve been working hard to get those first users on board, but it’s been quite challenging.

I’ve already tried the typical strategies that everybody talks about: cold email, LinkedIn InMail, careful targeting, decent copy. It’s mostly been a dead end. Low open rates, almost no replies.

At this point, I’m not looking for the usual advice you see in blog posts or on reddit. I’m specifically curious about unconventional or non-obvious things that actually worked for you early on, especially things that felt a bit scrappy, weird, or counterintuitive at the time.

If you’ve been through this phase, what genuinely worked and got you your first users?

Currently the GitHub status page says there is a "Major Outage" for GitHub Actions.

https://www.githubstatus.com/

This is as of 19:58 UTC / 11:58 PST on 2-Feb-2026

Wanted to gather some stories about people who were fired because of AI. Not a generic "reorg", what they say in the press release, but honestly, because of AI. Proves?

Facebook's feed is nonfunctional. Only some people get notification, even though they have notification for all messages turned on. Only some get the newest posts in their main feed. Sometimes I do get notifications, but only long after an urgent message was posted.

Has anybody successfully moved their local community off of Facebook groups?

I'm thinking about neighbor conversations/events, daycare, kindergarten, kids' classmates, sporting communities, etc.

If so, where did you go? Did you build something yourself or do you self-host some open source project? Did you find a good paid alternative?

I’ve been thinking about why dead code detection (and static analysis in general) feels so unreliable in Python compared to other languages. I understand that Python is generally dynamic in nature.

In theory it should be simple(again in theory): parse the AST, build a call graph, find symbols with zero references. In practice it breaks down quickly because of many things like:

1. dynamic dispatch (getattr, registries, plugin systems)

2. framework entrypoints (Flask/FastAPI routes, Django views, pytest fixtures)

3. decorators and implicit naming conventions

4. code invoked only via tests or runtime configuration

Most tools seem to pick one of two bad tradeoffs:

1. be conservative and miss lots of genuinely dead code

or

2. be aggressive and flag false positives that people stop trusting

What’s worked best for me so far is treating the code as sort of a confidence score, plus some layering in limited runtime info (e.g. what actually executed during tests) instead of relying on 100% static analysis.

Curious how others handle this in real codebases..

Do yall just accept false positives? or do yall ignore dead code detection entirely? have anyone seen approaches that actually scale? I am aware that sonarqube is very noisy.

I built a library with a vsce extension, mainly to explore these tradeoffs (link below if relevant), but I’m more interested in how others think about the problem. Also hope I'm in the right channel

Repo for context: https://github.com/duriantaco/skylos

I've been using Twitter / X for a good decade now, and while I've found it's a great place to connect with native app dev communities (I'm well connected with the React Native scene), I really struggle to connect with any web devs.

There are a few big names like Adam Wathan who are pretty active on Twitter of course, but considering how widespread web dev is, I see precious few up-and-coming web devs coding in public.

So, where are they? I have explored BlueSky a bit, but again it feels a bit like tumbleweeds (though maybe that's just my luck as a small account).

Are web devs more old-school, posting on bulletin boards and forums? Or is X still the answer, and I'm just getting aggressively packed into a different bubble?

… Or is it all realtime communication, like Slack and Discord, these days?

Especially interested in people using AI for brownfield development, but generally interested in if people are continuing down the spec driven path, or if agents + skills/prompts/mcp/agents.md/something else is filling the niche spec driven development was trying to capture.

Question was prompted by seeing spec kit have no commits for over a month an no obvious integration with GitHub’s new agents integration.

Hello those who still read forums.

I have recently graduated from a college and started working as a junior dev (trying to consume as much knowledge from senior colleagues as I can now) and it seems that the real world is kind of a different story compared to the college practice.

In the college we've been taught about design patterns and all these responsibilities like domain, application, infrastructure, UI. Domain should never depend on infrastructure or application layer and so on. But the projects I got have domain that depend on infrastructure and another one where application has a reference directly to infrastructure and been told that this is correct implementation... doh..

I think I was kind of a good at listening for the lectures, but I now am doubting about, whether it was worth learning stuff at all lol since it's so controversial out there. I am, of course, in no position to question senior dev, but what do you guys think - is it really normal that all the college so called "best practices" go straight to the trash bin or am I just misunderstanding the real-work-like context?

I’ve been building installs with addressable LED strips (5V, 12V, 24V). The same few failure modes show up over and over: dim tails on long runs, random sparkle or flicker, and connectors that become the weak point.

A few practices that helped me most:

Treat power distribution as the first design task: plan injection points early, keep feeder wires short, and avoid pushing all current through one end.

Always share a solid ground between controller and strip, and keep the data path simple. When runs get longer or environments get noisy, a small series resistor near the data source and a proper level shift (3.3V to 5V) often improves stability.

Assume connectors are “consumables”: strain relief matters, waterproofing needs to stay serviceable, and high current runs deserve more conservative choices.

I’m curious what your most reliable rules of thumb are for injection spacing, branch fusing, and debugging when things go wrong. If you have a checklist or measurement approach you trust, I’d love to learn it.

okay, so this is not so big to many of you , but today , i was just bored and tired of doing any marketing , cos nothing seemed to have been working. so i decided to do a search (i searched for quite a number of keywords) like error tracking for supabase , error tracking for next Js , but my saas didnt rank (if you dont know what im building , im working on a dead simple error tracker that notifies you when something breaks in prod, no bloated dashboards or config hell) , i built this cos sentry had too much noise and i just wanted something that lets me know when there's an issue in prod.

so i decided to do a search on "error tracking for shipfast(by marc lou)" and guess what ?? Bugmail was the first recommended result , now i dont know how this worked, i mean ive done some seo and stuff but i wasnt expecting it , and now i feel like im back , which is funny cos i didnt make a sale , i didnt onboard a new user yet i feel like o have conquered , life of a founder , i guess

i just wanted to share this here, also if you have any advice on how to rank higher on GSC and how to nail this marketing thing , any advice or feedback will be valuable

in the meantime , incase you want to check out what ive built;

you can check it out here ; https://www.bugmail.site

I am curious I am not sure if AI is just hype, I use it for software and a few other things. But looking at so many people talking about AGI when the best models can't even answer simple stuff correctly, fail at tool use, are vulnerable to all types of injection attacks that don't make sense.

I don't know if the investments in AI are worth it but am I blind for not seeing any hope for AGI any time soon.

Agentic AI is interesting perhaps but I hardly have had it work perfectly, I have to hold it's hand at everything.

People making random claims about AGI soon is really weakening my confidence in AI in general. Given I haven't seen much improvements in last few years other than better tools and wrappers, and models that work better with these tools and wrappers.

I'm one of the developers behind CiderStack. It's a local-first macOS VM tool for Apple devs who need clean installs, older Xcodes, or a safe place to test things without bricking their main machine. Spin up → snapshot → break things → delete → repeat. Why no subscription? CiderStack runs on your hardware. It doesn't need my servers. It doesn't phone home. So why would you pay me every month? I'm tired of SaaS fees for tools that could easily be a one-time purchase. Tired of losing access to software because a card expired. Tired of workflows held hostage behind subscriptions. Buy it once. Own it forever. Free updates for the major version. That's the deal. Who it's for:

Solo devs testing across macOS versions without buying multiple Macs IT admins safely testing betas and MDM profiles before rollout CI/CD teams spinning up ephemeral macOS runners Homelabbers with a rack of Mac minis (we built this for people like us)

14-day free trial, no account required. Just shipped v1.0.3 (found a few bugs pretty early on) Happy to answer questions.

especially for technical books with code

Currently, I’m working on a web app for managing documents, databases, and whiteboards—the typical app that aims to be like Notion.

However, right now I’m facing the dilemma of creating a plan with AI usage limits, since the idea is to make it more agentic: able to edit and query context across an entire workspace and move it into a document, for example, maybe draw something on a whiteboard, etc. Still, I have the feeling that consumption could easily get out of hand. I plan to use DeepSeek for AI chat, but use Gemini 3 Flash for agentic usage and editing because it’s more intelligent. Lately, I’ve seen how many core AI apps have shifted their pricing models from per-request pricing to a fixed usage limit, but I’m unsure whether that’s frowned upon, creates a less pleasant user experience, or maybe even gives the feeling that you’re not getting what you paid for. So I’d like to hear some opinions on what decision I should make.

I’m working on infrastructure to solve retry storms and outages. Before I go further, I want to understand what people are actually doing today. Compare solutions and maybe help someone see potential solutions. The problems:

Retry storms - API fails, your entire fleet retries independently, thundering herd makes it worse.

Partial outages - API is “up” but degraded (slow, intermittent 500s). Health checks pass, requests suffer.

What I’m curious about: ∙ What’s your current solution? (circuit breakers, queues, custom coordination, service mesh, something else?) ∙ How well does it work? What are the gaps? ∙ What scale are you at? (company size, # of instances, requests/sec)

I’d love to hear what’s working, what isn’t, and what you wish existed.

I'm someone who got into building/programming in early 2025, when vibe coding tools became more usable. Since then, I'd like to think that I have developed a lot as a programmer, but I still have this deep sense of imposter syndrome / worry that AI is too much of a crutch and I'm not really learning.

I have shipped a few projects, I always review AI-suggested code, do daily coding practice without AI, watch youtube videos, etc. but still don't know if I'm striking the right balance or whether I can really call myself a programmer.

I often see people say that the solution is to just fully learn to code without AI, (i.e, go "cold turkey"), which may be the best, but I wonder if the optimal path is somewhere in between given that AI is clearlly changing the game here in terms of what it means to be a programmer.

I'm curious how you have all handled this balancing act in the past few years. More concretely, what strategies do you use to both be efficient and able to ship / move quickly while ensuring you are also taking the time to really process and understand and learn what you are doing?